Data processing systems and methods for performing privacy assessments and monitoring of new versions of computer code for privacy compliance

ABSTRACT

In various embodiments, a data map generation system is configured to: (1) enable a user to specify one or more criteria; (2) identify one or more data flows based at least in part on the one or more specified criteria; (3) generate a data map based at least in part on the identified one or more data flows; and (4) display the data map to any suitable individual (e.g., the user). In particular embodiments, the system is configured to display all data flows associated with a particular organization that are stored within the system. In other embodiments, the system is configured to display all data flows that are associated with a particular privacy campaign undertaken by the organization.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional of U.S. patent application Ser. No. 15/883,041, filed Jan. 29, 2018, which is a continuation of U.S. patent application Ser. No. 15/671,073, filed Aug. 7, 2017, which is a divisional of U.S. patent application Ser. No. 15/254,901, filed Sep. 1, 2016, which claims priority from U.S. Provisional Patent Application Ser. No. 62/348,695, filed on Jun. 10, 2016; U.S. Provisional Patent Application Ser. No. 62/353,802, filed Jun. 23, 2016; and U.S. Provisional Patent Application Ser. No. 62/360,123, filed on Jul. 8, 2016, the entire disclosures of which are hereby incorporated by reference in their entirety.

TECHNICAL FIELD

This disclosure relates to data processing systems and methods for performing privacy assessments and monitoring new versions of computer code for updated features and conditions that relate to compliance with privacy standards.

BACKGROUND

Over the past years, privacy and security policies, and related operations have become increasingly important. Breaches in security, leading to the unauthorized access of personal data (which may include sensitive personal data) have become more frequent among companies and other organizations of all sizes. Such personal data may include, but is not limited to, personally identifiable information (PII), which may be information that directly (or indirectly) identifies an individual or entity. Examples of PII include names, addresses, dates of birth, social security numbers, and biometric identifiers such as a person's fingerprints or picture. Other personal data may include, for example, customers' Internet browsing habits, purchase history, or even their preferences (i.e., likes and dislikes, as provided or obtained through social media). While not all personal data may be sensitive, in the wrong hands, this kind of information may have a negative impact on the individuals or entities whose sensitive personal data is collected, including identity theft and embarrassment. Not only would this breach have the potential of exposing individuals to malicious wrongdoing, the fallout from such breaches may result in damage to reputation, potential liability, and costly remedial action for the organizations that collected the information and that were under an obligation to maintain its confidentiality and security. These breaches may result not only in financial loss, but loss of credibility, confidence, and trust from individuals, stakeholders, and the public.

Many organizations that obtain, use, and transfer personal data, including sensitive personal data, have begun to address these privacy and security issues. To manage personal data, many companies have attempted to implement operational policies and processes that comply with legal requirements, such as Mayada's Personal Information Protection and Electronic Documents Act (PIPEDA) or the U.S.'s Health Insurance Portability and Accountability Act (HIPPA) protecting a patient's medical information. The European Union's General Data Protection Regulation (GDPR) may fine companies up to 4% of their global worldwide turnover (revenue) for not complying with its regulations (companies must comply by March 2018). These operational policies and processes also strive to comply with industry best practices (e.g., the Digital Advertising Alliance's Self-Regulatory Principles for Online Behavioral Advertising).

Many regulators recommend conducting privacy impact assessments, or data protection risk assessments along with data inventory mapping. For example, the GDPR requires data protection impact assessments. Additionally, the United Kingdom ICO's office provides guidance around privacy impact assessments. The OPC in Mayada recommends personal information inventory, and the Singapore PDPA specifically mentions personal data inventory mapping. Thus, developing operational policies and processes may reassure not only regulators, but also an organization's customers, vendors, and other business partners.

For many companies handling personal data, privacy audits, whether done according to AICPA Generally Accepted Privacy Principles, or ISACA's IT Standards, Guidelines, and Tools and Techniques for Audit Assurance and Control Professionals, are not just a best practice, they are a requirement (for example, Facebook and Google will be required to perform 10 privacy audits each until 2032 to ensure that their treatment of personal data comports with the expectations of the Federal Trade Commission). When the time comes to perform a privacy audit, be it a compliance audit or adequacy audit, the lack of transparency or clarity into where personal data comes from, where it is stored, who is using it, where it has been transferred, and for what purpose is it being used, may bog down any privacy audit process. Even worse, after a breach occurs and is discovered, many organizations are unable to even identify a clear-cut organizational owner responsible for the breach recovery or provide sufficient evidence that privacy policies and regulations were complied with.

Many of these breaches have their roots in vulnerabilities that may be found in software applications, websites, or other computer code that collect, use and process personal data. The computer code may be an in-house application or solution, or one provided by a third party. When an organization's auditors or privacy team members conduct a privacy audit or assessment, they typically direct questions to software developers in an attempt to obtain answers they need to address compliance with privacy standards. Unfortunately, the auditors and developers do not always use the same vernacular or technical language. As an example, auditors might ask a developer, “List for me all the personal data that you collect,” or “are you using any third-party code?” A developer, when responding, might, for example, not understand that a user's IP address is considered personal data, especially according to some laws. A developer might also not understand that third party code includes, for example, including snippets of HTML for a hosted library from Google's hosted library, or the use of other software development kits (SDKs). With multitudes of questions during the audit process, the disconnect or language barrier may lead to vulnerabilities. Thus, auditors may ask a multitude of questions, but the disconnect from the language barrier might not lead to the identification or resolution of many privacy-related issues because the auditors are not obtaining the right answers to those questions.

In light of the above, there is currently a need for improved systems and methods for assessing mobile applications, websites, and other computer code for features and conditions that may have an impact on a company's compliance with privacy standards.

SUMMARY

In various embodiments, a computer-implemented data processing method for generating and displaying a data map of data related to one or more privacy campaigns comprises: (1) receiving a command to create a plurality of electronic records for each of one or more privacy campaigns; (2) creating a plurality of electronic records comprising a respective electronic record for each of the one or more privacy campaigns and digitally storing the plurality of records; (3) presenting on one or more graphical user interfaces a plurality of prompts for the input of campaign data related to each of the one or more privacy campaigns; (4) electronically receiving campaign data input by one or more users, wherein the campaign data relates to: (A) one or more types of personal data related to one or more of the one or more privacy campaigns; (B) a subject from which the personal data was collected; (C) the storage of the personal data; and (D) access to the personal data; (5) processing the campaign data by electronically associating the campaign data with each associated respective record for the one or more of the one or more privacy campaigns; (6) digitally storing the campaign data associated with each associated respective record for the one or more of the one or more privacy campaigns; (7) receiving a request to generate a data map, the request comprising one or more criteria; (8) identifying, based at least in part on the one or more criteria, one or more of the plurality of electronic records; (9) generating a data map based at least in part on the one or more identified plurality of electronic records; and (10) displaying the data map to a user.

In particular embodiments, a computer-implemented data processing method generating and displaying a data map of data related to one or more privacy campaigns comprises: (1) creating a plurality of electronic records for each of one or more privacy campaigns and digitally storing the plurality of electronic records, wherein the plurality of electronic records comprise a respective electronic record for each of the one or more privacy campaigns; (2) presenting on one or more graphical user interfaces a plurality of prompts for the input of campaign data related to each of the one or more privacy campaigns; (3) electronically receiving campaign data input by one or more users; (4) processing the campaign data by electronically associating the campaign data with each associated respective electronic record for the one or more of the one or more privacy campaigns; (5) digitally storing the campaign data associated with each associated respective record for the one or more of the one or more privacy campaigns; (6) receiving a request to generate a data map; (7) identifying, based at least in part on the one or more criteria, one or more of the plurality of electronic records; (8) generating a data map based at least in part on the one or more identified plurality of electronic records; and (9) displaying the data map to a user.

Additionally, in certain embodiments, a computer-implemented data processing method generating and displaying a data map of data related to one or more privacy campaigns comprises: (1) receiving a command to create a plurality of electronic records for each of one or more privacy campaigns; (2) creating a plurality of electronic records comprising a respective electronic record for each of the one or more privacy campaigns and digitally storing the plurality of records; (3) presenting on one or more graphical user interfaces a plurality of prompts for the input of campaign data related to each of the one or more privacy campaigns; (4) electronically receiving campaign data input by one or more users; (5) processing the campaign data by electronically associating the campaign data with each associated respective record for the one or more of the one or more privacy campaigns; (6) digitally storing the campaign data associated with each associated respective record for the one or more of the one or more privacy campaigns; (7) receiving a request to generate a data map where the request comprises one or more criteria; (8) identifying, based at least in part on the one or more criteria, one or more of the plurality of electronic records; (9) generating a data map based at least in part on the one or more identified plurality of electronic records; and (10) displaying the data map to a user.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments of a system and method for operationalizing privacy compliance and assessing risk of privacy campaigns are described below. In the course of this description, reference will be made to the accompanying drawings, which are not necessarily drawn to scale, and wherein:

FIG. 1 is a diagram illustrating an exemplary network environment in which various embodiments of the present system and methods for operationalizing privacy compliance may operate.

FIG. 2 is a schematic diagram of a computer (such as the server 120, or user device 140, 150, 160, 170, 180, 190) that is suitable for use in various embodiments;

FIG. 3 is a diagram illustrating an example of the different types of individuals that may be involved in privacy compliance.

FIG. 4 is a flow chart showing an example of a process performed by the system's Assessment Module.

FIG. 5 is a flow chart showing an example of a process performed by the system's Monitoring Module.

FIG. 6A is an example of a graphical user interface that shows the identification of the location of computer code.

FIG. 6B is an example of a graphical user interface that shows the identification of the location of computer code the results of an assessment.

FIG. 7 is an example of a graphical user interface that shows the results of the ongoing monitoring of computer code.

DETAILED DESCRIPTION

Various embodiments now will be described more fully hereinafter with reference to the accompanying drawings. It should be understood that the invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. Like numbers refer to like elements throughout.

Overview

Various systems and methods for operationalizing privacy compliance are described below. In particular, various systems are described below that automatically determine whether particular computer code (e.g., source code or compiled code) complies with one or more privacy policies. Such systems may operate with or without obtaining information from various users regarding the code.

In particular embodiments, the system is adapted to allow a user to provide the location of computer code (e.g., source code or compiled code) to be analyzed. This location may be, for example, a location (e.g., in local memory or on a third-party server, such as a server associated with an app store, such as Apple's App Store, or the Microsoft Store) of a particular software application or file. If the software code to be analyzed is that of a website, the location may be, for example, the web site's URL.

After the system receives the location of the code, the system may obtain the code by, for example, uploading the code from the specified location, or by scraping the relevant code from a specified website. The system then automatically analyzes the code to determine, for example, whether the code includes any functionality that would be relevant to one or more privacy policies. For example, the system may automatically determine whether the code, when executed, collects personal data in a way that is contrary to one or more applicable laws, and/or contrary to one or more other privacy policies that apply to the code.

As a particular example, the system may analyze the computer code to determine whether the code, when executed, gathers any personal information (such as sensitive personal information) regarding the user in a manner that is contrary to: (1) any applicable law; (2) a privacy policy of a privacy campaign that the software code is being implemented in conjunction with (See U.S. Provisional Patent Application 62/348,695, which, as noted above, is incorporated herein by reference in its entirety, for a more detailed discussion of privacy campaigns); (3) a general privacy policy of an organization implementing the computer code; and/or (4) any contractual provisions (e.g., software terms and conditions) that apply to the code.

In a particular embodiment, the system may use suitable third-party software to determine whether the code, when executed, gathers any personal information. In other embodiments, the system may do so without using third party software.

In various embodiments, upon determining that particular code gathers personal information, the system may send a request to a first user for information as to why the code includes the functionality at issue and whether the functionality could potentially be omitted. For example, if the system determines that the code, when executed, tracks the user's location (e.g., the user's longitude and latitude, the zip code that they're located in, etc.) or web browsing habits, the system may present one or more prompts to a user to input: (1) why the system is tracking the user's location; (2) whether the location-tracking functionality could be omitted from the code, or modified to reduce the resolution of the location-tracking functionality (e.g., reduced from tracking the user's precise longitude and latitude to more generally tracking the zip code or other territorial boundary that they are located in) without having a negative impact on the business purpose of the code; (3) why the system is tracking the user's browsing habits; and/or (4) whether the browser-tracking functionality could be omitted from the code without having a negative impact on the business purpose of the code. The system may present such questions to any suitable user such as, for example: (a) a software developer that is associated with developing the code; (b) an “owner” of a software campaign associated with the code; (c) a privacy officer; and/or (d) an auditor.

The system may then transmit an alert to one or more specified individuals (e.g., indicating that the code includes functionality that may be in violation of one or more applicable privacy policies) along with the answers to the questions referenced above. The specified individuals may then use the answers to determine whether to coordinate modifying the code to comply with the applicable privacy policies (e.g., privacy laws or internal privacy policies).

In particular embodiments, the system may include a Monitoring Module for monitoring a particular piece of software to determine whether the software has changed. If the software changes, the system may, for example: (1) send an alert to an appropriate individual (e.g., a privacy officer) indicating that the software has changed (e.g., a new version of the software has been released); and/or (2) analyze the new version of the code (e.g., as described above) to determine whether the new version of the code violates any applicable privacy policies. The appropriate individual may then take any necessary action to assure compliance with the applicable privacy policies (e.g., coordinate revision of the code and/or a downgrade to the immediate previous version of the code). Various embodiments are described in greater detail below.

In particular embodiments, the system may also, or alternatively, be adapted to scan predetermined software code to automatically determine whether the code, when executed, collects or otherwise uses personal information (e.g., sensitive personal information) and, if so, what types of personal information are being collected. In various embodiments, in response to determining that the code collects certain predetermined types of personal information, the system may associate a particular risk level with the code (and/or a privacy campaign associated with the code) and/or flag the code (and/or a privacy campaign associated with the code) to indicate that, before the code is placed into use (e.g., publicly launched and/or a non-testing version of the software version of the software is launched), the code needs to: (1) be modified to not collect one or more types of personal information; and/or (2) be reviewed and approved by an appropriate individual or group (e.g., the individual or group must approve the code including the attribute). Such risk levels and flags may be communicated to users within the context of a risk assessment system, such as one or more of the systems described in U.S. Provisional Patent Application Ser. No. 62/348,695, entitled “Data Processing Systems and Methods for Operationalizing Privacy Compliance and Assessing the Risk of Various Respective Privacy Campaigns and Related Systems and Methods”, which was filed on Jun. 10, 2016, and which, as noted above, is incorporated herein by reference in its entirety.

Exemplary Technical Platforms

As will be appreciated by one skilled in the relevant field, a system for performing privacy assessments and monitoring new versions of computer code for updated features and conditions that relate to compliance with privacy standards may be embodied as a computer system, a method, or a computer program product. Accordingly, various embodiments may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, particular embodiments may take the form of a computer program product stored on a computer-readable storage medium having computer-readable instructions (e.g., software) embodied in the storage medium. Various embodiments may take the form of, for example, web, mobile, or wearable computer-implemented computer software. Any suitable computer-readable storage medium may be utilized including, for example, hard disks, compact disks, DVDs, optical storage devices, and/or magnetic storage devices.

Various embodiments are described below with reference to block diagrams and flowchart illustrations of methods, apparatuses (e.g., systems) and computer program products. It should be understood that each step of the block diagrams and flowchart illustrations, and combinations of steps in the block diagrams and flowchart illustrations, respectively, may be implemented by a computer executing computer program instructions. These computer program instructions may be loaded onto a general-purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions which execute on the computer or other programmable data processing apparatus to create means for implementing the functions specified in the flowchart step or steps.

These computer program instructions may also be stored in a computer-readable memory that may direct a computer or other programmable data processing apparatus to function in a particular manner such that the instructions stored in the computer-readable memory produce an article of manufacture that is configured for implementing the function specified in the flowchart step or steps. The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions that execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart step or steps.

Accordingly, steps of the block diagrams and flowchart illustrations support combinations of mechanisms for performing the specified functions, combinations of steps for performing the specified functions, and program instructions for performing the specified functions. It should also be understood that each step of the block diagrams and flowchart illustrations, and combinations of steps in the block diagrams and flowchart illustrations, may be implemented by special purpose hardware-based computer systems that perform the specified functions or steps, or combinations of special purpose hardware and other hardware executing appropriate computer instructions.

Example System Architecture

FIG. 1 is a block diagram of a System 100 according to a particular embodiment. As may be understood from this figure, the System 100 includes one or more computer networks 110, a Server 120, a Storage Device 130 (which may contain one or more databases of information), one or more remote client computing devices such as a tablet computer 140, a desktop or laptop computer 150, or a handheld computing device 160, such as a cellular phone, browser and Internet capable set-top boxes 170 connected with a TV 180, or a smart TV 180 having browser and Internet capability. The client computing devices attached to the network may also include copiers/printers 190 having hard drives. The Server 120, client computing devices, and Storage Device 130 may be physically located in a central location, such as the headquarters of the organization, for example, or in separate facilities. The devices may be owned or maintained by employees, contractors, or other third parties (e.g., a cloud service provider). In particular embodiments, the one or more computer networks 115 facilitate communication between the Server 120, one or more client computing devices 140, 150, 160, 170, 180, 190, and Storage Device 130.

The one or more computer networks 115 may include any of a variety of types of wired or wireless computer networks such as the Internet, a private intranet, a public switched telephone network (PSTN), or any other type of network. The communication link between the Server 120, one or more client computing devices 140, 150, 160, 170, 180, 190, and Storage Device 130 may be, for example, implemented via a Local Area Network (LAN) or via the Internet.

Example Computer Architecture Used within the System

FIG. 2 illustrates a diagrammatic representation of the architecture of a computer 200 that may be used within the System 100, for example, as a client computer (e.g., one of computing devices 140, 150, 160, 170, 180, 190, shown in FIG. 1), or as a server computer (e.g., Server 120 shown in FIG. 1). In exemplary embodiments, the computer 200 may be suitable for use as a computer within the context of the System 100 that is configured to operationalize privacy compliance and assess the risk of privacy campaigns. In particular embodiments, the computer 200 may be connected (e.g., networked) to other computers in a LAN, an intranet, an extranet, and/or the Internet. As noted above, the computer 200 may operate in the capacity of a server or a client computer in a client-server network environment, or as a peer computer in a peer-to-peer (or distributed) network environment. The computer 200 may be a personal computer (PC), a tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), a cellular telephone, a web appliance, a server, a network router, a switch or bridge, or any other computer capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that computer. Further, while only a single computer is illustrated, the term “computer” shall also be taken to include any collection of computers that individually or jointly execute a set (or multiple sets) of instructions to perform, for example, any one or more of the methodologies discussed herein.

An exemplary computer 200 includes a processing device 202, a main memory 204 (e.g., read-only memory (ROM), flash memory, dynamic random-access memory (DRAM) such as synchronous DRAM (SDRAM) or Rambus DRAM (RDRAM)), a static memory 206 (e.g., flash memory or static random-access memory (SRAM)), and a data storage device 218, which communicate with each other via a bus 232.

The processing device 202 represents one or more general-purpose processing devices such as a microprocessor, a central processing unit, or the like. More particularly, the processing device 202 may be a complex instruction set computing (CISC) microprocessor, reduced instruction set computing (RISC) microprocessor, very long instruction word (VLIW) microprocessor, or processor implementing other instruction sets, or processors implementing a combination of instruction sets. The processing device 202 may also be one or more special-purpose processing devices such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), network processor, or the like. The processing device 202 may be configured to execute processing logic 226 for performing various operations and steps discussed herein.

The computer 200 may further include a network interface device 208. The computer 200 also may include a video display unit 210 (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)), an alphanumeric input device 212 (e.g., a keyboard), a cursor control device 214 (e.g., a mouse), and a signal generation device 216 (e.g., a speaker). The data storage device 218 may include a non-transitory computer-readable storage medium 230 (also known as a non-transitory computer-readable storage medium or a non-transitory computer-readable medium) on which is stored one or more sets of instructions 222 (e.g., software, software modules) embodying any one or more of the methodologies or functions described herein. The software 222 may also reside, completely or at least partially, within main memory 204 and/or within processing device 202 during execution thereof by computer 200—main memory 204 and processing device 202 also constituting computer-accessible storage media. The software 222 may further be transmitted or received over a network 220 via a network interface device 208.

While the computer-readable storage medium 230 is shown in an exemplary embodiment to be a single medium, the terms “computer-readable storage medium” and “machine-accessible storage medium” should be understood to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term “computer-readable storage medium” should also be understood to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by the computer and that cause the computer to perform, for example, any one or more of the methodologies of the present invention. The term “computer-readable storage medium” should accordingly be understood to include, but not be limited to, solid-state memories, optical and magnetic media, etc.

Exemplary System Platform

According to various embodiments, the processes and logic flows described in this specification may be performed by a system (e.g., System 100) that includes, but is not limited to, one or more programmable processors (e.g., processor 202) executing one or more computer program modules to perform functions by operating on input data and generating output, thereby tying the process to a particular machine (e.g., a machine programmed to perform the processes described herein). This includes processors located in one or more of client computers (e.g., client computers 140, 150, 160, 170, 180, 190 of FIG. 1). These devices connected to network 110 may access and execute one or more Internet browser-based program modules that are “served up” through the network 110 by one or more servers (e.g., server 120 of FIG. 1), and the data associated with the program may be stored on one or more storage devices, which may reside within a server or computing device (e.g., Main Memory 204, Static Memory 206), be attached as a peripheral storage device to the one or more servers or computing devices, or attached to the network (e.g., Storage 130).

The System 100 may facilitate the acquisition, storage, maintenance, use, and retention of campaign data associated with a plurality of privacy campaigns within an organization. In doing so, various aspects of the System 100 initiate and create a plurality of individual data privacy campaign records that are associated with a variety of privacy-related attributes and assessment-related metadata for each campaign. These data elements may include, for example: the subjects of the sensitive information, the respective person or entity responsible for each campaign (e.g., the campaign's “owner”), the location where the personal data will be stored, the entity or entities that will access the data, the parameters according to which the personal data will be used and retained, the Risk Level associated with a particular campaign (as well as assessments from which the Risk Level is calculated), an audit schedule, and other attributes and metadata.

The System 100 may also be adapted to facilitate the setup and auditing of each privacy campaign. Suitable modules for performing this functionality may include, for example, an Assessment Module and a Monitoring Module (examples of which are described below). It is to be understood that these are examples of modules of various embodiments, but the functionalities performed by each module as described may be performed by more (or fewer) modules. Further, the functionalities described as being performed by one module may be performed by one or more other modules.

A. Example Elements Related to Privacy

FIG. 3 provides a high-level visual overview of example “subjects” for particular data privacy assessments, exemplary “owners,” various elements related to the storage and access of personal data, and elements related to the use and retention of the personal data. Each of these elements may, in various embodiments, be accounted for by the System 100 as it facilitates the implementation of an organization's privacy compliance policy.

As may be understood from FIG. 3, sensitive information may be collected by an organization from one or more subjects 300. Subjects may include customers whose information has been obtained by the organization. For example, if the organization is selling goods to a customer, the organization may have been provided with a customer's credit card or banking information (e.g., account number, bank routing number), social security number, or other sensitive information.

An organization may also possess personal data originating from one or more of its business partners. Examples of business partners are vendors that may be data controllers or data processors. Vendors may supply a component or raw material to the organization, which may include software applications or database programs, or a website. Vendors may also be outside contractors responsible, for example, for the marketing or legal work of the organization. The personal data acquired from the partner may be that of the partners, or even that of other entities collected by the partners. For example, a marketing agency may collect personal data on behalf of the organization and transfer that information to the organization. Moreover, the organization may share personal data with one of its partners. For example, the organization may provide a marketing agency with the personal data of its customers so that it may conduct further research.

Other subjects 300 include the organization's own employees. Organizations with employees often collect personal data from their employees, including address and social security information, usually for payroll purposes, or even prior to employment, for conducting credit checks. The subjects 300 may also include minors. It is noted that various corporate privacy policies or privacy laws may require that organizations take additional steps to protect the sensitive privacy of minors.

Still referring to FIG. 3, within an organization, one or more particular individuals (or a particular group of individuals) may be designated to be an “owner” who is in charge of particular “privacy campaigns.” A privacy campaign may be, for example, an organized effort to manage personal data obtained from a particular initiative, such as a particular business initiative, that may utilize personal data collected from one or more persons or entities. The owners 310 may have any suitable role within the organization. In various embodiments, an owner of a particular campaign will have primary responsibility for the campaign and will serve as a resident expert regarding the personal data obtained through the campaign, and the way that the data is obtained, stored, and/or accessed. As shown in FIG. 3, an owner may be a member of any suitable department, including the organization's marketing, Human Resources, Research and Development, or Information Technology department. As will be described below, an organization may employ personnel from a privacy team, who typically operate under the chief privacy officer, or auditors, to carry out privacy assessments or audits.

Referring still to FIG. 3, this figure shows that the use and retention 315 of personal data may include how the data is analyzed and used within the organization's operations, whether the data is backed up, and which parties within the organization are supporting the campaign.

The system may also be configured to help manage the storage and access 320 of personal data. As shown in FIG. 3, a variety of different parties may access the data, and the data may be stored in any of a variety of different locations, including on-site, or in “the cloud”, i.e., on remote servers that are accessed via the Internet or other suitable network.

B. Assessment Module

As noted above, the system may include an Assessment Module for automatically performing privacy assessments of computer code. FIG. 4 illustrates an exemplary process 400, executed by an Assessment Module, for automatically performing privacy assessments of computer code. The process may be executed by one or more computing devices of the System 100. In exemplary embodiments, a server (e.g., server 140) in conjunction with a client computing device having a browser (e.g., computing devices 140, 150, 160, 170, 180, 190) execute the Assessment Module by communicating, as needed, via a network (network 110). In various exemplary embodiments, the Assessment Module may call upon other modules to perform certain functions. In exemplary embodiments, the software may be organized as a single module to perform various computer executable routines.

As mentioned above, disconnects and differences in vernacular might lead to wrong answers to questions during a privacy audit or assessment. To address this issue, in various embodiments, instead of determining whether an organization complies with the defined parameters of a privacy campaign by, for example, conducting an audit as described above (e.g., by asking users to answer questions regarding the privacy campaign, such as: (1) “What personal data is being collected”; or (2) “What cookies are being used on the website”, the system (e.g., by executing the Assessment Module) may be configured to automatically determine whether the organization is complying with one or more aspects of the privacy policy. For example, during the audit process, the system may: (1) obtain a copy of computer code (e.g., a software application or an “app”) that is collecting and/or using sensitive user information, and then (2) automatically analyze the app to determine whether the operation of the app or website is complying with the terms of the privacy campaign (the privacy assessment standards at issue) that govern the use of the app, website, or other code.

The process of FIG. 4 begins at step 405. The system then advances to step 410, where it displays, on a graphical user interface (e.g., a webpage or dialog box), an instruction (e.g., one or more prompts) for a user to provide the location of computer code, which may be, for example, the code for a software application (e.g., a mobile application) or website, or any other computer code. The user may then, for example, browse to the location of a file that includes the computer code for uploading. If the code involved is that for a website, the system may prompt the user to provide the URL of the website.

At step 415, the Assessment Module may then use the location provided by the user to obtain the computer code (for example, by uploading the file, or obtaining the code directly from a website (e.g., by “scraping” the code from the website)).

Next, at step 420, the Assessment Module automatically electronically analyzes the computer code to determine a plurality of privacy-related attributes of the computer code. The privacy-related attributes (features and/or conditions) of the computer code may relate, for example, to the types of personal information the computer code collects and/or accesses. For example, a particular app may have one or more of the following privacy-related attributes: (1) uses location-based services to detect the location of the user's computing device (e.g., services that may determine the precise longitude and latitude of the user's computing device and/or which of a plurality of predetermined geographical areas the computing device is located in—e.g., the particular U.S. State or Zip Code that the user's computing device is located in); (2) places network calls to another country (e.g., a particular designated country, such as China); (3) uses encryption to protect personal data; (4) issues calls to third party software; (5) accesses communications logs (e.g., call logs, email); (6) uses cookies to track user behavior; and/or (7) collects personal data (e.g., a user's social security number, date of birth, credit card number, physical address, mailing address, email address, IP address, Internet browsing habits, purchase history, biometric data (e.g., finger prints, retinal scans, or other biometric data), and/or personal preferences). The system may use, for example, static analysis, behavior analysis, or some combination of the two, to make the analysis and determination.

The Assessment Module may integrate with a third-party system or software (e.g., Veracode), which executes the analysis. As an example, for a software application, after the app is uploaded to the system, the system detects what privacy permissions and data the app is collecting from users.

In response to determining that the app is collecting one or more specified types of personal data, which may be sensitive information (e.g., the location of the user's mobile device), the Assessment Module may automatically request follow up information from the user by posing one or more questions to the user. In the exemplary method of FIG. 4, at step 425, the system may electronically display to the user a list of the privacy-related attributes related to the computer code, wherein each displayed attribute relates to a privacy assessment standard (e.g., privacy policy, privacy law). For example, code related to the collection of personal data such as a person's IP address, may be governed by particular privacy laws.

At step 430, the system may electronically display one or more prompts to the user, wherein each prompt informs the user to input information regarding the attributes. Questions posed by the prompts may include, for example: (1) “For what business reason is the data being collected?”; (2) “How is the app user's consent given to obtain the data?”; (3) “Would app users be surprised that the data is being collected?”; (4) “Is the data encrypted at rest and/or in motion?”; (5) “What would happen if the system did not collect this data?”; and/or (6)“What business impact would it have to not collect this data?” In various embodiments, the system is adapted to allow users to customize these follow-up questions, but the system asks the questions (e.g., the same questions, or a customized list of questions) for each privacy issue that is found for the computer code at issue. The system may also collect other relevant comments regarding the computer code.

At step 435, the information regarding the attributes that were input by the user may be communicated to one or more second users (e.g., one or more software developers, privacy officers, “owners” of the code, or auditors) for an assessment. The information may, for example, help a privacy officer work with a software developer to modify the code to comply with one or more privacy policies, or to draft or modify a privacy policy to be used on a website that implements the code. At step 440, the process 400 may end.

As noted above, in particular embodiments, the system may also, or alternatively, be adapted to scan predetermined software code to automatically determine whether the code, when executed, collects or otherwise uses personal information (e.g., sensitive personal information) and, if so, what types of personal information are being collected. In various embodiments, in response to determining that the code collects certain predetermined types of personal information, the system may associate a particular risk level with the code and/or flag the code to indicate that, before the code is placed into use (e.g., before the code is publicly launched and/or before a non-testing version of the code is launched), the code needs to: (1) be modified to not collect one or more types of personal information; and/or (2) be reviewed and approved by an appropriate individual or group (e.g., the individual or group must approve the code including the attribute). Such risk levels and flags may be communicated to users within the context of a risk assessment system, such as one or more of the systems described in U.S. Provisional Patent Application Ser. No. 62/348,695, entitled “Data Processing Systems and Methods for Operationalizing Privacy Compliance and Assessing the Risk of Various Respective Privacy Campaigns and Related Systems and Methods”, which was filed on Jun. 10, 2016, and which, as noted above, is incorporated herein by reference in its entirety.

C. Monitoring Module

In various embodiments, after particular computer code is scanned a first time, if the code is subsequently scanned, the system may only scan to code to determine whether any changes have been made to the code since the immediate previous scan of the code. If so, the system may, for example, automatically scan the application, as discussed above, to determine whether the code has changed to add any additional privacy-related attributes. The system may then, for example, automatically notify one or more designated individuals (e.g., privacy office representatives) to indicate that a new version of the app was detected and also inform the one or more designated individuals as to whether the new version of the code added any additional privacy-related attributes since the immediate previous version of the code. In particular embodiments, the notification may also indicate whether the new version of the app was released without a privacy assessment having been performed on the new version.

In particular embodiments, when configuring the desired operation of the Monitoring Module, a user may specify that, if the system identifies a new version of a particular piece of code and determines that the new version of the code has added one or more additional privacy-related attributes, the system will automatically prompt a user (e.g., as discussed above) for information regarding the newly-added privacy-related attributes. The system may then use this information as discussed above (e.g., it may send the information to a privacy officer or other individual who is responsible for the privacy aspects of the computer code).

Various steps executed by the Monitoring Module are shown in the flowchart of FIG. 5. Turning to this figure, the process 500 begins at step 505. Next, at step 510, the system may receive an electronic input from the user indicating that they wish to have the system monitor particular computer code for changes.

At step 515, the system prompts for and receives from the user an electronic input identifying the location of the new versions of computer code. In various embodiments, the system is adapted to (optionally) automatically monitor (e.g., continuously monitor) locations that may be one or more online software application marketplaces (such as the Microsoft Store, the Google Play Store, or Apple's App Store) to determine whether the application has changed (e.g., a new version of the application is available).

In various embodiments in which the computer code comprises a website, the location may be a website's URL, and the Monitoring Module may prompt the user to enter the URL of the web site to be analyzed. For example, the Monitoring Module may prompt the user to “Provide the URL of the Website to be Monitored.”

While the system may analyze every directory or level in the website, the system may, optionally, separately monitor, for changes in the content of a web page that includes the privacy policy that applies to the website.

Often, an organization's privacy team (privacy office) and/or legal department may provide web developers with the terms of the privacy policy. However, it is not uncommon for an organization's marketing team or outside creative agency to take it upon themselves to make changes by rewording the policy, or repositioning content on a particular web page. Because the location, placement, wording, and/or content of privacy policies may be governed by law, there is reason to monitor changes to both the content of such privacy policies and their placement on related web pages. Monitoring the privacy page of a website may be beneficial, for example, in Mexico, which requires the content of the policy to contain the word “privacy” and for that word to be displayed in the bottom right hand portion of the policy page.

At step 520, the Monitoring Module monitors the identified location for any new instances (i.e., potential new versions) of the computer code. If the system detects a new instance of the computer code located in the identified location, it compares the obtained instance of computer code to a previous assessed version of the computer code (e.g., the most recent version of the computer code that was previously assessed by the system). During this scanning, the Monitoring Module may also determine any privacy-related attributes of the computer code. In the case of a website, the Monitoring Module may, for example, continuously monitor the specified website site for cookies, and/or for whether other tracking mechanisms, such as fingerprinting technologies and/or 3rd party SDKs, are used.

At step 525, the Monitoring Module uses the analyzed information to compare the code that was obtained with a previously assessed version of the computer code. At 530, the Monitoring Module determines whether the currently-obtained instance of computer code is different than the previously assessed version of the computer code (which would be indicative of a new version of the software). In various embodiments related to monitoring of a privacy policy link, the Monitoring Module may also auto-detect whether any changes have been made to the privacy policy or the location of the privacy policy link on the page.

If no differences are detected, then the process 500 may proceed back to step 520 wherein the Monitoring Module monitors for new instances of computer code again. If there is a difference between the obtained instance and the immediate previously assessed version of the computer code, then at 535, the system may notify a user that a change in versions of the software code has been detected and prompt the user to obtain information regarding the new version of computer code (e.g., the reason for the new code, whether the new code is necessary, etc.).

Alternatively, at step 535, the Monitoring Module may automatically analyze the computer code and electronically present the user with a list of differences between the obtained instance of computer code and the previous assessed version of the computer code. For example, the Monitoring Module may prompt the user for information regarding the privacy-related attributes that have changed or been added. In various embodiments, the Monitoring Module may ask the user to complete a series of one or more follow-up questions for each of these changed or added privacy-related attributes found during the scan of the app, or website. For example, the system may ask the reason the new privacy-related attribute is in the code, whether the code may be changed back to eliminate the attribute, etc.

At 540, any information obtained from step 535 may be communicated to one or more second users (e.g., one or more software developers, privacy officers, or auditors) for use in further privacy-related decision-making as described above. In various embodiments, the system is configured to, for example, generate an alert to an appropriate individual (e.g., a designated privacy officer) to inform them of the change(s) to the computer code and provide them with the obtained information regarding the changes as described above.

At 545, appropriate changes to the code may be made to comply with privacy standards if the campaign owners decide that the computer code is noncompliant. The privacy officer may use this information, for example, to determine whether to modify the privacy policy for the website or to coordinate discontinuing use of the new tracking technologies and/or SDKs. and, in response to auto-detecting such changes, trigger an audit of the project.

Exemplary User Experience

FIGS. 6A and 6B illustrates an example of a graphical user interface (GUI) for performing automated privacy assessments. The method includes displaying on an Assessment GUI 600 (e.g., a webpage or dialog box) an instruction 605 (or prompts) for a user to provide the location of computer code, which may be, for example, a software application (e.g., a mobile application, a database application), or a website. For example, the system may prompt a user with an “Upload Your Software or Enter the URL of the Website to Initiate Privacy Assessment” message. The user may use the browse button 610 to browse to the location of a file that includes the computer code for uploading. When the file is selected, the name of the file may appear in a computer code entry field 615 so as to display to the user the file that will be uploaded. If the code involved is a website, the user may provide the URL of the website for which the privacy assessment is desired. Once the user selects the “Extract” button 620, the system electronically obtains the computer code. The “Extract” button 620 may, alternatively, bear another label, such as “Import,” “Upload,”, “Obtain,” etc.

The system then automatically electronically analyzes the computer code to determine one or more attributes of the computer code. The attributes (features and/or conditions) of the computer code may relate to location-based services, network calls to another country (e.g., China), encryption (or lack thereof), third party software (e.g., libraries, SDKs), access to communications logs (e.g., call logs, email), tracking (e.g., cookies), and personal data collection (wherein the personal data may be a social security number, date of birth, credit card number, physical address, mailing address, email address, IP address, Internet browsing habits, purchase history, biometric data (e.g., finger prints or retinal scans), and personal preferences. The system may use, for example, static analysis, behavior analysis, or some combination of the two, to make the analysis and determination.

Next, as shown in illustrative FIG. 6B, the system may electronically display to the user, in assessment GUI 600, a list of the attributes related to the computer code, wherein each displayed attribute relates to a privacy assessment standard (e.g., privacy policy, privacy law). The assessment GUI 600 may display, for example, an identifier (e.g., a file name) associated with the computer code 625 that was assessed (if the assessment involved a website, the URL of the website may be displayed). The assessment GUI 600 may also display some informative indication 630 to the user that the analysis revealed certain features or conditions (e.g., attributes) of the code that may have an impact on one or more of the company's privacy polies (or relevant privacy laws). In example 6B, the system may electronically display a list of attributes 635, along with a plurality of prompts to the user, wherein each prompt informs the user to input information regarding the attributes, and other relevant comments. As mentioned above, a user may be prompted to answer a plurality of questions, including for each attribute. In the exemplary embodiment show in FIG. 6B, the user is presented with a prompt 640 to enter the reason the code has the attribute, a prompt 645 to select whether the attribute may be eliminated (e.g., check “Yes” or “No”), and a prompt 650 to enter in any comments or exceptions relating to the attribute. Each prompt may have one or more entry fields, check boxes, and the like, associated with it. The information regarding the attributes that was input by the user may be communicated to one or more second users (e.g., software developers, privacy office personnel, or auditors) for an assessment. In the example shown, the user may select the submit button 665 to communicate this information.

In the example shown in FIG. 6b , prior to selecting the submit button 665, a user of the system (e.g., or software developer, a privacy office team member, or auditor,) may respond to the prompt 655 by electing to automatically monitor subsequent computer code versions of the code by selecting the check box associated with the prompt 655. The system may display a prompt 660 asking for the user to input the location of the new versions of computer code. In various embodiments, a drop-down selector may be used to facilitate entering the location, which may be an on-line application store, such as the Microsoft Store, Google Play Store, Apple App Store, or in the case of a website, a URL. The system then periodically (or in the alternative, continuously) monitors the identified location for any instances (e.g., potential new versions) of the computer code. The system then compares code obtained from the location to a previous assessed version of the computer code.

FIG. 7: Collaborator Assignment Notification and Description Entry

Referring to FIG. 7, if an obtained instance of computer code is different than the immediate previously privacy-assessed version of the computer code, then the system may display a GUI 700 that shows the results of the analysis and prompts for and obtains information regarding any new or changed attributes discovered. The GUI 700 may display the name 705 of the new version (if a name and version number was detected), as well as the name 710 of the previous version of the computer code. The GUI 700 may provide an informative statement 715 indicating, for example, “We detected the following new version of your software. The following changes or added features/conditions may relate to our company's privacy policies. Please provide information to the privacy office regarding each.” In various exemplary embodiments, the monitoring module may simply ask the user for information regarding the new version of computer code (e.g., the reason for the new code). The system may display a prompt that states, for example, “We have detected a new version of software from the original. Please let us know what has changed.”

The system may also, after analyzing the computer code for differences, present the user with a list of differences, and obtain information regarding the attributes that have changed or been added. In Example 7, the system may electronically display a list of attributes 720 (here, only one attribute is listed—“Access to phone photos”), along with a plurality of prompts to the user, where each prompt informs the user to input information regarding the attributes, and other relevant comments. As mentioned above, numerous questions may be prompted, including for each attribute. In the exemplary embodiment shown in FIG. 7, the user is presented with a prompt 725 to enter the reason the attribute is in the code, a prompt 730 to select whether the attribute may be eliminated (e.g., check “Yes” or “No”), and a prompt 735 to enter in any comments or exceptions relating to the attribute. Each prompt may have one or more entry fields, check boxes, and the like, associated with it. The information regarding the attributes that was input by the user may be communicated (e.g., notified, alerted, etc.) to one or more second users (e.g., privacy office personnel, auditors, etc.) for an assessment. In the example shown, the user may select the submit button 740 to communicate this information to the one or more second users (e.g., privacy office personnel, auditors, etc.) for use in determining how to move forward in accordance with the applicable privacy policies.

CONCLUSION

Although embodiments above are described in reference to various systems and methods for performing privacy assessments and monitoring new versions of computer code for updated features and conditions that relate to compliance with privacy standards, it should be understood that various aspects of the system described above may be applicable to other privacy-related systems, or to other types of systems, in general. While this specification contains many specific embodiment details, these should not be construed as limitations on the scope of any invention or of what may be claimed, but rather as descriptions of features that may be specific to particular embodiments of particular inventions. Certain features that are described in this specification in the context of separate embodiments may also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment may also be implemented in multiple embodiments separately or in any suitable sub-combination. Moreover, although features may be described above as acting in certain combinations and even initially claimed as such, one or more features from a claimed combination may in some cases be excised from the combination, and the claimed combination may be directed to a sub-combination or variation of a sub-combination.

Similarly, while operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In certain circumstances, multitasking and parallel processing may be advantageous. Moreover, the separation of various system components in the embodiments described above should not be understood as requiring such separation in all embodiments, and it should be understood that the described program components and systems may generally be integrated together in a single software product or packaged into multiple software products.

Many modifications and other embodiments of the invention will come to mind to one skilled in the art to which this invention pertains having the benefit of the teachings presented in the foregoing descriptions and the associated drawings. While examples discussed above cover the use of various embodiments in the context of operationalizing privacy compliance and assessing risk of privacy campaigns, various embodiments may be used in any other suitable context. Therefore, it is to be understood that the invention is not to be limited to the specific embodiments disclosed and that modifications and other embodiments are intended to be included within the scope of the appended claims. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for the purposes of limitation. 

What is claimed is:
 1. A computer-implemented data processing method for generating and displaying a data map of data related to one or more privacy campaigns, the method comprising: receiving a command to create a plurality of electronic records for each of one or more privacy campaigns; creating a plurality of electronic records comprising a respective electronic record for each of the one or more privacy campaigns and digitally storing the plurality of records; presenting on one or more graphical user interfaces a plurality of prompts for the input of campaign data related to each of the one or more privacy campaigns; electronically receiving campaign data input by one or more users, wherein the campaign data relates to: one or more types of personal data related to one or more of the one or more privacy campaigns; a subject from which the personal data was collected; and one or more parameters under which the personal data will be retained; processing the campaign data by electronically associating the campaign data with each associated respective record for the one or more of the one or more privacy campaigns; digitally storing the campaign data associated with each associated respective record for the one or more of the one or more privacy campaigns; receiving a request to generate a data map, the request comprising one or more criteria; identifying, based at least in part on the one or more criteria, one or more of the plurality of electronic records; generating a data map based at least in part on the one or more identified plurality of electronic records; and displaying the data map to a user.
 2. The computer-implemented data processing method of claim 1, wherein the user comprises a privacy officer.
 3. The computer-implemented data processing method of claim 1, wherein the one or more criteria are selected from the group consisting of: a first criteria to generate a data map based at least in part on a particular privacy campaign of the one or more privacy campaigns; a second criteria to generate a data map based at least in part on a particular piece of the campaign data; and a third criteria to generate a data map based at least in part on each of the one or more privacy campaigns.
 4. The computer-implemented data processing method of claim 3, wherein: the one or more criteria comprise the first criteria; and identifying the one or more of the plurality of electronic records comprises identifying each particular electronic record that stores the campaign data for the particular privacy campaign.
 5. The computer-implemented data processing method of claim 4, wherein generating the data map comprises: retrieving the campaign data from each of the identified plurality of electronic records; and generating a visual representation of the particular privacy campaign that includes the campaign data from each of the identified plurality of electronic records.
 6. The computer-implemented data processing method of claim 3, wherein: the one or more criteria comprise the second criteria; identifying the one or more of the plurality of electronic records comprises identifying each particular electronic record that stores the particular piece of the campaign data.
 7. The computer-implemented data processing method of claim 6, wherein generating the data map comprises: retrieving one or more pieces of campaign data from each of the identified plurality of electronic records; and generating a visual representation of the one or more pieces of campaign data from the one or more identified plurality of electronic records.
 8. The computer-implemented data processing method of claim 6, wherein the visual representation of the one or more pieces of campaign data from the one or more identified plurality of electronic records comprises: a source of the one or more pieces of campaign data; a storage destination for the one or more pieces of campaign data; and one or more entities that have accesses to the one or more pieces of campaign data.
 9. The computer-implemented data processing method of claim 3, wherein: the one or more criteria comprise the third criteria; and generating the data map comprises: identifying the one or more of the plurality of electronic records that comprises campaign data for the one or more privacy campaigns; retrieving the campaign data from each of the one or more of the plurality of electronic records; and generating a visual representation of the campaign data from each of the one or more of the plurality of electronic records.
 10. The computer-implemented data processing method of claim 1, wherein the method further comprises substantially automatically generating and continuously updating the data map in response to receiving the campaign data.
 11. A computer-implemented data processing method for generating and displaying a data map of data related to one or more privacy campaigns, the method comprising: creating a plurality of electronic records for each of one or more privacy campaigns and digitally storing the plurality of electronic records, wherein the plurality of electronic records comprise a respective electronic record for each of the one or more privacy campaigns; presenting on one or more graphical user interfaces a plurality of prompts for the input of campaign data related to each of the one or more privacy campaigns; electronically receiving campaign data input by one or more users, wherein the campaign data relates to: one or more types of sensitive information related to one or more of the one or more privacy campaign; the storage of the sensitive information; and access to the sensitive information; processing the campaign data by electronically associating the campaign data with each associated respective electronic record for the one or more of the one or more privacy campaigns; digitally storing the campaign data associated with each associated respective record for the one or more of the one or more privacy campaigns; receiving a request to generate a data map, the request comprising one or more criteria that are selected from the group consisting of: a first criteria to generate a data map based at least in part on a particular privacy campaign of the one or more privacy campaigns; a second criteria to generate a data map based at least in part on a particular piece of the campaign data; and a third criteria to generate a data map based at least in part on each of the one or more privacy campaigns; identifying, based at least in part on the one or more criteria, one or more of the plurality of electronic records; generating a data map based at least in part on the one or more identified plurality of electronic records; and displaying the data map to a user.
 12. The computer-implemented data processing method of claim 11, wherein the user comprises a privacy officer.
 13. The computer-implemented data processing method of claim 11, wherein: the one or more criteria comprise the first criteria; and identifying the one or more of the plurality of electronic records comprises identifying each particular electronic record that stores the campaign data for the particular privacy campaign.
 14. The computer-implemented data processing method of claim 13, wherein generating the data map comprises: retrieving the campaign data from each of the identified plurality of electronic records; and generating a visual representation of the particular privacy campaign that includes the campaign data from each of the identified plurality of electronic records.
 15. The computer-implemented data processing method of claim 11, wherein: the one or more criteria comprise the second criteria; identifying the one or more of the plurality of electronic records comprises identifying each particular electronic record that stores the particular piece of the campaign data.
 16. The computer-implemented data processing method of claim 15, wherein generating the data map comprises: retrieving one or more pieces of campaign data from each of the identified plurality of electronic records; and generating a visual representation of the one or more pieces of campaign data from the one or more identified plurality of electronic records.
 17. The computer-implemented data processing method of claim 15, wherein the visual representation of the one or more pieces of campaign data from the one or more identified plurality of electronic records comprises: a source of the one or more pieces of campaign data; a storage destination for the one or more pieces of campaign data; and one or more entities that have accesses to the one or more pieces of campaign data.
 18. The computer-implemented data processing method of claim 11, wherein: the one or more criteria comprise the third criteria; and generating the data map comprises: identifying the one or more of the plurality of electronic records that comprises campaign data for the one or more privacy campaigns; retrieving the campaign data from each of the one or more of the plurality of electronic records; and generating a visual representation of the campaign data from each of the one or more of the plurality of electronic records.
 19. A computer-implemented data processing method for generating and displaying a data map of data related to one or more privacy campaigns, the method comprising: receiving a command to create a plurality of electronic records for each of one or more privacy campaigns; creating a plurality of electronic records comprising a respective electronic record for each of the one or more privacy campaigns and digitally storing the plurality of records; presenting on one or more graphical user interfaces a plurality of prompts for the input of campaign data related to each of the one or more privacy campaigns; electronically receiving campaign data input by one or more users, wherein the campaign data is related to at least one selected from a group consisting of: one or more types of personal data related to one or more of the one or more privacy campaigns; a subject from which the personal data was collected; one or more entities responsible for the one or more privacy campaigns the storage of the personal data; and access to the personal data; processing the campaign data by electronically associating the campaign data with each associated respective record for the one or more of the one or more privacy campaigns; digitally storing the campaign data associated with each associated respective record for the one or more of the one or more privacy campaigns; receiving a request to generate a data map, the request comprising one or more criteria that is selected from the group consisting of: a first criteria to generate a data map based at least in part on a particular privacy campaign of the one or more privacy campaigns; a second criteria to generate a data map based at least in part on a particular piece of the campaign data; and a third criteria to generate a data map based at least in part on each of the one or more privacy campaigns; identifying, based at least in part on the one or more criteria, one or more of the plurality of electronic records; generating a data map based at least in part on the one or more identified plurality of electronic records; and displaying the data map to a user.
 20. The computer-implemented data processing method of claim 19, wherein the method further comprises substantially automatically generating and continuously updating the data map in response to receiving the campaign data. 